The other new supervisor for Queens’ this term is Fawad Jamshed. Fawad will be supervising the 1B students for Artificial Intelligence I.
Here’s a bit of text about Fawad’s background:
Hi My name is Fawad Jamshed. My research interests include evolutionary computation modelling and multimodal neuroimaging analysis. Evolutionary computing is to develop computers programs using similar rules as that are used by human brain. If we want to make computers intelligent, best way to do this is to copy human brain (i.e. most intelligent entity known). A major problem in this regard is that we do not know much about how human brain works. There are number of neuroimaging studies that use number of different methods to test different assumptions about human brain to understand it’s working.
I hold undergraduate degree in Computer Science, postgraduate degree in business Information technology and PhD in Computer Science (Artificial Intelligence). Currently, I am working in the Neurolex group at the department of experimental Psychology, University of Cambridge. My current research involves, analysing neuroimaging data from functional magnetic resonance (FMRI) along with magnetoencephalography (MEG) and electroencephalography (EEG) experiments.
When an area of the brain is in use, blood flow to that region also increases. FMRI uses technology that measures brain activity by detecting associated changes in blood flow. MEG is a functional neuroimaging technique for mapping brain activity by recording magnetic fields produced by electrical currents occurring naturally in the brain. EEG is the recording of electrical activity along the scalp. EEG measures voltage fluctuations resulting from ionic current flows within the neurons of the brain. Aim of this research is to develop understanding about how human brain works, by relating cognitive theories to the underlying neural systems.
My PhD thesis title was “A basic Framework for Grounding Symbols by using Cell Assemblies that Emerges from Simulated Neurons”. During my PhD, main goal of my research was to develop an artificially intelligent agent that can understand meanings of different words like humans do so to effectively perceive and interact with its surrounding environment. A more biological faithful neuron model (fatigue leaky, integrating and firing neurons, fLIF), were develop to build an agent that can communicates via natural language, senses the environment, and assists the user. A 3D game was developed and an artificial agent was modelled in the game to check how intelligently it can behave using algorithms that was designed.